CS Demo Analyzer vs SC2 Replay AI Coach

CS Demo Analyzer is a free command-line tool for analyzing and exporting Counter-Strike 2 and CS:GO demo files. It produces CSV, JSON, or CSDM output, and an optional flag adds entity positions such as player and grenade locations. Users can force a demo source, with supported options including FACEIT, ESEA, ESL, and Valve. Developers can use the Go API to analyze a demo or analyze and export it. The @akiver/cs-demo-analyzer NPM module wraps the Go CLI and supplies TypeScript types and constants. The project uses the demoinfocs-golang parser, created by Markus W. and maintained by him and AkiVer. It is distributed under the MIT License, which permits use, modification, and distribution subject to its conditions. The linked CS Demo Manager companion application lists statistics, grenade finding, heatmaps, VAC tracking, video generation, downloads, search, and exports; that app can export XLSX or JSON or provide SQL access to its database. CS Demo Analyzer is intended for developers extracting data from Counter-Strike demos and supports Linux, macOS, Windows, and API use.

SC2 Replay AI Coach is a free browser-based site for parsing, viewing, and analyzing StarCraft II and Brood War replay files. It accepts .SC2Replay files for StarCraft II and .rep files for Brood War. Replay pages present economy timelines, army composition, battle records, build-order timelines, strategy classifications, and coaching notes. The automated post-game coach reads replay events, derives economy and combat metrics, compares openings with known build patterns, and adds notes tied to replay timestamps. Deterministic rules identify tactics including drops, cannon rushes, proxies, fast expansions, and one-base all-ins. Uploaded replays remain available through shareable URLs, with listed team coverage from 1v1 through 4v4. The tool requires no account or download and states no replay-count limit. Uploading is available in desktop browsers where local replay files are stored. Co-op replay visualization is supported, but ladder-coaching assumptions do not fully fit commander-specific units and mission objectives. Frame-perfect micro grading is limited because replay data contains events and sampled positions rather than a full coaching video.